curl --request POST \
  --url https://api.getflex.ai/v1/fine_tunes/create_finetune \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "name": "<string>",
  "model": "<string>",
  "dataset_id": "<string>",
  "n_epochs": 123,
  "train_with_lora": true,
  "batch_size": 123,
  "wandb_key": "<string>",
  "learning_rate": 123,
  "n_checkpoints_and_evaluations_per_epoch": 1,
  "save_only_best_checkpoint": false,
  "lora_config": {},
  "early_stopping_config": {}
}
'

import requests

url = "https://api.getflex.ai/v1/fine_tunes/create_finetune"

payload = {
    "name": "<string>",
    "model": "<string>",
    "dataset_id": "<string>",
    "n_epochs": 123,
    "train_with_lora": True,
    "batch_size": 123,
    "wandb_key": "<string>",
    "learning_rate": 123,
    "n_checkpoints_and_evaluations_per_epoch": 1,
    "save_only_best_checkpoint": False,
    "lora_config": {},
    "early_stopping_config": {}
}
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    name: '<string>',
    model: '<string>',
    dataset_id: '<string>',
    n_epochs: 123,
    train_with_lora: true,
    batch_size: 123,
    wandb_key: '<string>',
    learning_rate: 123,
    n_checkpoints_and_evaluations_per_epoch: 1,
    save_only_best_checkpoint: false,
    lora_config: {},
    early_stopping_config: {}
  })
};

fetch('https://api.getflex.ai/v1/fine_tunes/create_finetune', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.getflex.ai/v1/fine_tunes/create_finetune",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'name' => '<string>',
    'model' => '<string>',
    'dataset_id' => '<string>',
    'n_epochs' => 123,
    'train_with_lora' => true,
    'batch_size' => 123,
    'wandb_key' => '<string>',
    'learning_rate' => 123,
    'n_checkpoints_and_evaluations_per_epoch' => 1,
    'save_only_best_checkpoint' => false,
    'lora_config' => [
        
    ],
    'early_stopping_config' => [
        
    ]
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.getflex.ai/v1/fine_tunes/create_finetune"

	payload := strings.NewReader("{\n  \"name\": \"<string>\",\n  \"model\": \"<string>\",\n  \"dataset_id\": \"<string>\",\n  \"n_epochs\": 123,\n  \"train_with_lora\": true,\n  \"batch_size\": 123,\n  \"wandb_key\": \"<string>\",\n  \"learning_rate\": 123,\n  \"n_checkpoints_and_evaluations_per_epoch\": 1,\n  \"save_only_best_checkpoint\": false,\n  \"lora_config\": {},\n  \"early_stopping_config\": {}\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Authorization", "Bearer <token>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.getflex.ai/v1/fine_tunes/create_finetune")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"name\": \"<string>\",\n  \"model\": \"<string>\",\n  \"dataset_id\": \"<string>\",\n  \"n_epochs\": 123,\n  \"train_with_lora\": true,\n  \"batch_size\": 123,\n  \"wandb_key\": \"<string>\",\n  \"learning_rate\": 123,\n  \"n_checkpoints_and_evaluations_per_epoch\": 1,\n  \"save_only_best_checkpoint\": false,\n  \"lora_config\": {},\n  \"early_stopping_config\": {}\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.getflex.ai/v1/fine_tunes/create_finetune")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"name\": \"<string>\",\n  \"model\": \"<string>\",\n  \"dataset_id\": \"<string>\",\n  \"n_epochs\": 123,\n  \"train_with_lora\": true,\n  \"batch_size\": 123,\n  \"wandb_key\": \"<string>\",\n  \"learning_rate\": 123,\n  \"n_checkpoints_and_evaluations_per_epoch\": 1,\n  \"save_only_best_checkpoint\": false,\n  \"lora_config\": {},\n  \"early_stopping_config\": {}\n}"

response = http.request(request)
puts response.read_body

{
  "id": "<string>",
  "config": {},
  "user_id": "<string>",
  "model_id": "<string>",
  "name": "<string>",
  "checkpoints_count": 123,
  "total_steps": 123,
  "dataset_id": "<string>",
  "engine_data": {
    "runpod_run_id": "<string>"
  }
}

{
  "error": 123,
  "message": "<string>"
}

{
  "error": 123,
  "message": "<string>"
}